Data hiding in grayscale images by dynamic programming based on a human visual model

[[abstract]]A new method for data hiding in grayscale images based on a human vision model with distortion-minimizing capabilities is proposed. Each of the eight bit planes of an input grayscale image is viewed as a binary image, into which message data are embedded horizontally. Two optimization techniques, namely, block pattern coding and dynamic programming, are proposed for image distortion minimization. Experimental results show good performs of the proposed method. (C) 2009 Elsevier Ltd. All rights reserved

Data hiding in grayscale images by dynamic programming based on a human visual model

[[abstract]]A new method for data hiding in grayscale images based on a human vision model with distortion-minimizing capabilities is proposed. Each of the eight bit planes of an input grayscale image is viewed as a binary image, into which message data are embedded horizontally. Two optimization techniques, namely, block pattern coding and dynamic programming, are proposed for image distortion minimization. Experimental results show good performs of the proposed method. © 2009 Elsevier Ltd. All rights reserved

Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach

This paper proposes a probabilistic approach for the detection and the tracking of particles in fluorescent time-lapse imaging. In the presence of a very noised and poor-quality data, particles and trajectories can be characterized by an a contrario model, that estimates the probability of observing the structures of interest in random data. This approach, first introduced in the modeling of human visual perception and then successfully applied in many image processing tasks, leads to algorithms that neither require a previous learning stage, nor a tedious parameter tuning and are very robust to noise. Comparative evaluations against a well-established baseline show that the proposed approach outperforms the state of the art.Comment: Published in Journal of Machine Vision and Application

Data Hiding in Gray-Scale Images by LSB Method using IWT with Lifting Scheme

This paper introduced a completely unique steganography technique to extend the capability and therefore the physical property of the image once embedding. Genetic rule utilized to get associate degree optimum mapping operate to minimize the error distinction between the quilt and therefore the stego image and use the block mapping technique to preserve the native image properties. Additionally we have a tendency to applied the OPAP to extend the activi ty capability of the rule comp are d to different systems. However, the process complexity of the new rule is high. The simulation results showed that capability and physical property of image had enl arg ed timing. Also, we will choose the most effective blo ck size to scale back the computation value and to extend the PSNR victimisation optimisation algorithms like GA

A review and open issues of multifarious image steganography techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method

Application of Stochastic Diffusion for Hiding High Fidelity Encrypted Images

Cryptography coupled with information hiding has received increased attention in recent years and has become a major research theme because of the importance of protecting encrypted information in any Electronic Data Interchange system in a way that is both discrete and covert. One of the essential limitations in any cryptography system is that the encrypted data provides an indication on its importance which arouses suspicion and makes it vulnerable to attack. Information hiding of Steganography provides a potential solution to this issue by making the data imperceptible, the security of the hidden information being a threat only if its existence is detected through Steganalysis. This paper focuses on a study methods for hiding encrypted information, specifically, methods that encrypt data before embedding in host data where the ‘data’ is in the form of a full colour digital image. Such methods provide a greater level of data security especially when the information is to be submitted over the Internet, for example, since a potential attacker needs to first detect, then extract and then decrypt the embedded data in order to recover the original information. After providing an extensive survey of the current methods available, we present a new method of encrypting and then hiding full colour images in three full colour host images with out loss of fidelity following data extraction and decryption. The application of this technique, which is based on a technique called ‘Stochastic Diffusion’ are wide ranging and include covert image information interchange, digital image authentication, video authentication, copyright protection and digital rights management of image data in general

Steganography-based secret and reliable communications: Improving steganographic capacity and imperceptibility

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Unlike encryption, steganography hides the very existence of secret information rather than hiding its meaning only. Image based steganography is the most common system used since digital images are widely used over the Internet and Web. However, the capacity is mostly limited and restricted by the size of cover images. In addition, there is a tradeoff between both steganographic capacity and stego image quality. Therefore, increasing steganographic capacity and enhancing stego image quality are still challenges, and this is exactly our research main aim. Related to this, we also investigate hiding secret information in communication protocols, namely Simple Object Access Protocol (SOAP) message, rather than in conventional digital files. To get a high steganographic capacity, two novel steganography methods were proposed. The first method was based on using 16x16 non-overlapping blocks and quantisation table for Joint Photographic Experts Group (JPEG) compression instead of 8x8. Then, the quality of JPEG stego images was enhanced by using optimised quantisation tables instead of the default tables. The second method, the hybrid method, was based on using optimised quantisation tables and two hiding techniques: JSteg along with our first proposed method. To increase the steganographic capacity, the impact of hiding data within image chrominance was investigated and explained. Since peak signal-to-noise ratio (PSNR) is extensively used as a quality measure of stego images, the reliability of PSNR for stego images was also evaluated in the work described in this thesis. Finally, to eliminate any detectable traces that traditional steganography may leave in stego files, a novel and undetectable steganography method based on SOAP messages was proposed. All methods proposed have been empirically validated as to indicate their utility and value. The results revealed that our methods and suggestions improved the main aspects of image steganography. Nevertheless, PSNR was found not to be a reliable quality evaluation measure to be used with stego image. On the other hand, information hiding in SOAP messages represented a distinctive way for undetectable and secret communication.The Ministry of Higher Education in Syria and the University of Alepp

PIRANHA: an engine for a methodology of detecting covert communication via image-based steganography

In current cutting-edge steganalysis research, model-building and machine learning has been utilized to detect steganography. However, these models are computationally and cognitively cumbersome, and are specifically and exactly targeted to attack one and only one type of steganography. The model built and utilized in this thesis has shown capability in detecting a class or family of steganography, while also demonstrating that it is viable to construct a minimalist model for steganalysis. The notion of detecting steganographic primitives or families is one that has not been discussed in literature, and would serve well as a first-pass steganographic detection methodology. The model built here serves this end well, and it must be kept in mind that the model presented is posited to work as a front-end broad-pass filter for some of the more computationally advanced and directed stganalytic algorithms currently in use. This thesis attempts to convey a view of steganography and steganalysis in a manner more utilitarian and immediately useful to everyday scenarios. This is vastly different from a good many publications that treat the topic as one relegated only to cloak-and-dagger information passing. The subsequent view of steganography as primarily a communications tool useable by petty information brokers and the like directs the text and helps ensure that the notion of steganography as a digital dead-drop box is abandoned in favor of a more grounded approach. As such, the model presented underperforms specialized models that have been presented in current literature, but also makes use of a large image sample space (747 images) as well as images that are contextually diverse and representative of those seen in wide use. In future applications by either law-enforcement or corporate officials, it is hoped that the model presented in this thesis can aid in rapid and targeted responses without causing undue strain upon an eventual human operator. As such, a design constraint that was utilized for this research favored a False Negative as opposed to a False Positive - this methodology helps to ensure that, in the event of an alert, it is worthwhile to apply a more directed attack against the flagged image